The Bkper Agent doesn't just scan documents—it reads the document and learns your specific bookkeeping patterns. When you correct a Transaction, it learns from this edit and rewrites its understanding to handle future cases similarly. By your third bank statement upload, the Agent is auto-assigning accounts with 90%+ accuracy based on your actual transaction history.
You've downloaded another bank statement. 47 lines. Each one needs categorization. You know this will take the rest of your afternoon—clicking through menus and dropdowns, verifying accounts, just to make sure they are categorized the same way as last month.
Traditional document processing (invoices, receipts, csv files) chains you to scanning, verification, manual data entry, validation, consolidation, and approval—multiple handoffs where errors hide and time disappears. The Bkper Agent collapses this into one streamlined cycle: upload the file, post the extracted transactions, “check” what's correct, edit what needs adjustment. 10 minutes and that's it, as each correction trains the Agent, improving accuracy toward 99% direct posting where future statements require less and less editing towards no editing at all.
Bank Statements, receipts, invoices, etc. become Transactions inside your book, where the Agent sees your Chart of Accounts, can analyze your existing transactions, and discovers patterns in your financial history. When processing an "Office Supplies" invoice, it is aware of your past Transactions to know how office purchases were categorized—then assigns the same Accounts for you.
The Agent searches your existing bookkeeping to discover account assignment patterns. It understands that your "Uber to airport" transactions get assigned differently than "Uber to client meeting" because it sees how you've categorized them before.
When you correct Transactions, the Agent doesn't just remember that one fix, it analyzes the failure, generates improved extraction instructions, validates them, and updates itself. This structured learning goes beyond simple pattern matching.
No procedures to replicate or configure when your business grows. Simply drag and drop documents into any book—the Agent learns from that book's transaction history independently. Automate uploads across multiple entities without rebuilding workflows or retraining systems.
Team members, departments, clients, or other peers can upload their documents directly to a book shared with them, eliminating the bottleneck of centralized document collection. Delegate responsibility to whoever has the receipts or statements, while the Agent ensures extraction quality and learning across all contributors.
Bank statements with 100 transactions, specialized vendor invoices with custom fields, photo receipts—each gets processed with appropriate logic. One system that adapts to your actual mix of document types, all learning independently.
Start uploading documents immediately. The Agent learns from your existing transactions—no merchant databases to configure, no category mappings to set up, no rules to define. It discovers your patterns from actual bookkeeping.
Unlike external document processors that push data to accounting software, the Bkper Agent operates within Bkper books where it has access to your complete financial context. Categorization decisions are made with full understanding of your Charts of Accounts and Transaction history.
Each book learns independently with complete data isolation, and you maintain full control to delete files anytime. Google Gemini LLMs interpret documents through secure authenticated API calls, and your documents are never used to train public AI models.
